500 words in length and should focus on connecting the concepts learned in the 2 modules and readings to your experiences in everyday life (e.g., conversations with family and friends o

May 15, 2018 Circulation. 2018;137:2166–2178. DOI: 10.1161/CIRCULATIONAHA.117.0296522166

William M. Schultz, MD Heval M. Kelli, MD John C. Lisko, MD Tina Varghese, MD Jia Shen, MD Pratik Sandesara, MD Arshed A. Quyyumi, MD Herman A. Taylor, MD Martha Gulati, MD John G. Harold, MD Jennifer H. Mieres, MD Keith C. Ferdinand, MD George A Mensah, MD Laurence S. Sperling, MD

ABSTRACT: Socioeconomic status (SES) has a measurable and significant effect on cardiovascular health. Biological, behavioral, and psychosocial risk factors prevalent in disadvantaged individuals accentuate the link between SES and cardiovascular disease (CVD). Four measures have been consistently associated with CVD in high-income countries: income level, educational attainment, employment status, and neighborhood socioeconomic factors. In addition, disparities based on sex have been shown in several studies. Interventions targeting patients with low SES have predominantly focused on modification of traditional CVD risk factors. Promising approaches are emerging that can be implemented on an individual, community, or population basis to reduce disparities in outcomes. Structured physical activity has demonstrated effectiveness in low-SES populations, and geomapping may be used to identify targets for large-scale programs. Task shifting, the redistribution of healthcare management from physician to nonphysician providers in an effort to improve access to health care, may have a role in select areas. Integration of SES into the traditional CVD risk prediction models may allow improved management of individuals with high risk, but cultural and regional differences in SES make generalized implementation challenging. Future research is required to better understand the underlying mechanisms of CVD risk that affect individuals of low SES and to determine effective interventions for patients with high risk. We review the current state of knowledge on the impact of SES on the incidence, treatment, and outcomes of CVD in high-income societies and suggest future research directions aimed at the elimination of these adverse factors, and the integration of measures of SES into the customization of cardiovascular treatment.

© 2018 American Heart Association, Inc.

IN DEPTH

Socioeconomic Status and Cardiovascular Outcomes Challenges and Interventions

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Circulation

Key Words: cardiovascular diseases ◼ epidemiology ◼ social class ◼ social determinants of health ◼ risk factors

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Cardiovascular diseases (CVDs) remain the lead- ing cause of death from chronic disease in the United States and worldwide despite remark-

able advances made in the past century. CVD accounts for nearly 1 in 3 deaths in the United States despite a 25.3% decrease in age-standardized deaths attributed to CVD from 2004 to 2014.1 Traditional CVD risk fac- tors have been identified, including hypertension, dys- lipidemia, diabetes mellitus, family history of premature coronary heart disease (CHD), and smoking; however, the contribution of social determinants of health, as best represented by socioeconomic status (SES), to CVD risk is poorly understood. Low SES has been linked to the development of CVD and may confer a cardiovas- cular risk that is equivalent to traditional risk factors.2,3 The increased burden of CVD in people with low SES is attributable to a constellation of biological, behavioral, and psychosocial risk factors that are more prevalent in disadvantaged individuals.4,5

Established interventions exist for addressing SES- related determinants of health and health inequities.6 Several interventions have been evaluated to improve health disparities attributable to social inequity, but results are inconsistent.7 Better understanding of SES and risk stratification are critical first steps in identifying and tailoring interventions to improve CVD risk in the population. We review the current state of knowledge on the impact of SES on the incidence, treatment, and outcomes of CVD in high-income societies and suggest future research directions aimed at the elimination of these adverse factors, and the integration of measures of SES into the customization of cardiovascular treat- ment, as well.

OVERVIEW OF SOCIOECONOMIC FACTORS The factors that constitute an individual’s SES vary be- tween location and culture.8–10 Four markers for SES have demonstrated an association with CVD in high-in- come countries (HIC): income level, educational attain- ment, employment status, and environmental factors (Figure 1).11–17 Although many factors have been used as surrogates for SES, these particular markers are ad- vantageous because of their ease of collection by ques- tionnaire in addition to the substantial existing litera- ture characterizing their association with clinical CVD outcomes. In addition, it is unlikely that a single marker of SES is adequate in predicting CVD risk because of the interactions between SES factors, regional variations in SES associations with CVD, and the dynamic changes between SES markers and CVD outcomes throughout an individual’s life course.8,11,18

Low- and middle-income countries (LMICs) carry ≈80% of the global burden of CVD.19 However, studies

evaluating the association between SES and cardiovas- cular health in LMICs are limited and often contain con- flicting findings.10,20 Furthermore, the association of SES and CVD in LMICs cannot be extrapolated from stud- ies in HICs; obesity is an epidemic among the impover- ished in HICs, but is a disease of the rich in low-income countries because of the increased access to a Western diet.21 Characterization of the impact of SES in LMICs will require additional high-quality prospective studies and is beyond the scope of this review.

INCOME LEVEL Income level has been consistently associated with CVD risk.11,12 A large study in the United States and Finland found an increased risk of nonfatal myocardial infarction and sudden cardiac death in the low-income cohorts that persisted after adjusting for smoking and alcohol consumption.12 The results may be applicable at both an individual and neighborhood level.22 Gerber et al22 found that each $10 000 increase in median income of a neigh- borhood reduced mortality risk in the group by 10%.

A study of >15 000 patients admitted for acute myocardial infarction (AMI) or CHD in the Nether- lands found that individuals in the lower quintiles of income had significantly higher rates of 28-day and 1-year mortality.23 Increased mortality was also shown for the lowest-income quartile in comparison with the highest-income quartile in a cohort presenting with ST-segment–elevation myocardial infarction (hazard ratio, 1.17; 95% confidence interval, 1.11–1.25).24 Residents in low-income areas were less likely to re- ceive a left heart catheterization within 24 hours of a ST-segment–elevation myocardial infarction or within

Figure 1. Markers of socioeconomic status.

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48 hours of a non–ST-segment–elevation myocardial infarction than patients from high-income areas.24 The authors of this study posited that the difference may be attributable to the perception that low-income individuals would be less likely to comply with criti- cal post–percutaneous coronary intervention medica- tions (eg, antiplatelet agents) or that low-income pa- tients were less likely to be offered more expensive procedures (eg, drug-eluting stents).24 The mortality difference between income groups in the study was attenuated after adjustment for time to left heart catheterization.24 Increased mortality rates were also present in patients from low-income areas in Taiwan, a HIC with universal health care, who were hospitalized with AMI.25

Mortality differences in low-income patients may be driven in part by disparities in standards of care. Low- income patients in the Netherlands were less likely to undergo interventions, including percutaneous coro- nary intervention, when presenting with AMI.23 Cardiac rehabilitation, a proven therapy to reduce mortality and hospital readmissions after AMI,26,27 is less likely to be attended or completed by individuals from low-income areas after hospitalization for CHD, percutaneous coronary intervention, or coronary artery bypass graft surgery.28 Studies have also demonstrated that statin medications were less likely to be initiated after AMI in low-income individuals.29,30 Men with low incomes were less likely to receive other guideline-recommend- ed medications, including β-blockers and angiotensin- converting enzyme inhibitors, but the association was attenuated in women.30

The substandard care may be explained in part by decreased access to quality care in the socially disad- vantaged.31–33 Lack of access to quality care has been shown to increase heart failure and post-AMI hospital readmission rates in the United States,33 and patients with financial barriers to health care had fewer yearly medical checkups, were less likely to use aspirin, and were at higher risk of future CVD events.32

Low-income individuals in Taiwan undergoing coro- nary artery bypass graft received lower-quality care and experienced higher mortality than the high-income co- hort.31 France, like Taiwan, has a national health sys- tem but still faces inequalities in access to primary care and coronary revascularizations in low-income areas.34 These studies highlight the difficulty in providing equal care to a patient population regardless of income. In- equalities in access to care, interventions, and prescrib- ing practices will need to be addressed before care be- comes equivalent between social groups.

EDUCATIONAL ATTAINMENT The inverse relationship between educational attain- ment and CVD in HIC has been known for decades,

and new population-based studies continue to provide insight into the strength of the association and its un- derlying mechanisms.13,35 A large study by Woodward et al35 analyzed nearly 90 000 individuals in Australia and New Zealand and found that those with a primary education had an increased risk of CVD, cardiovascular mortality, and all-cause mortality in comparison with individuals with a tertiary education. Higher education was associated with increased alcohol consumption and inversely related to smoking, blood pressure, cho- lesterol levels, and diabetes mellitus.35

Several studies have also demonstrated a higher risk of AMI in individuals with a lower educational level.36–38 Lower educational attainment also predicts worse short- term (30 days) and long-term (≥1 year) outcomes after AMI.22,39–41 Of the several socioeconomic factors exam- ined in a cohort of patients from South Korea, only low education (≤6 years of schooling) was associated with increased risk of cardiac events or all-cause mortality.41 Patients with low SES tend to have an increased num- ber of comorbidities but receive fewer interventions.40,42 Despite their increased comorbidities, individuals with a lower education level were less likely to be referred to tertiary prevention programs, including cardiac rehabili- tation, than those who had a higher education level.42

Educational attainment may affect health in several ways. Individuals with less education tend to have an increased number of CVD risk factors.5 An analysis in the Netherlands by Kershaw et al43 demonstrated that a majority (56.6%) of CHD risk in individuals with low education was attributable to behavioral and biologi- cal risk factors. The most significant contributors were smoking (27.3%), obesity (10.2%), physical inactivity (6.3%), and hypertension (5.3%).43 Hu et al36 deter- mined that approximately half of the increased risk of incident AMI in low education groups was explained by traditional risk factors. Even with these estimates, the mechanisms underlying the remainder of the increased risk associated with low educational attainment remain to be determined.

A potential contributor to CVD risk is the strong cor- relation between education and health literacy.44,45 In- dividuals with poor health literacy are more likely to be noncompliant with their medications46 and experience increased all-cause mortality.47 The association between health literacy and outcomes may be partially mediated by poor reading comprehension, which has an indirect effect on CHD risk.48 The absolute effect of health lit- eracy and reading comprehension on CVD risk requires further characterization, but may be an area for inter- vention in individuals with low education attainment. It is also important to note that although studies looking at the impact of SES on outcomes adjust for variables such as traditional risk factors, there is potential for re- sidual confounding that may be contributing to adverse health that is not accounted for in the models.

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EMPLOYMENT STATUS Employment is a commonly used marker of SES, and unemployment has been associated with increased risk of CVD.11,14,49 Analysis by Méjean et al49 demon- strated a 20% increase in risk of CHD events in an unemployed French population without preexisting heart disease (hazard ratio, 1.20; confidence interval, 1.04–1.39) after adjustment for age, sex, diet, and lifestyle. A large proportion (46%) of the CHD risk is explained by dietary and lifestyle mediators, most notably alcohol consumption (17%) and smoking (13%).49

A recent study of individuals with high SES relative to the general population also demonstrated an in- creased risk of cardiovascular events in the unemployed despite extensive adjustment for covariates, including age, sex, biological characteristics, behavioral vari- ables, and socioeconomic factors.14 The outcomes of the unemployed population in the study were worse than those of the retired cohort, which suggests that the detrimental effect of unemployment may be driven by the job loss itself.14 An alternative explanation is that those with poor health may be more likely to become unemployed. Nonetheless, it is important to note that unemployment is associated with increased CVD bur- den in the socially advantaged, and in those with low SES at baseline, as well.

Dupre et al50 performed a comprehensive study on the relationship between employment status and risk for AMI in the United States. Unemployment was as- sociated with a 35% increased risk for AMI (hazard ratio, 1.35; confidence interval, 1.10–1.66) within the first year, after which time the risk disappeared.50 The cumulative number of job losses was associated with an incremental increase in AMI risk, and the cumulative time spent unemployed was also significantly associ- ated with increased risk for AMI.50 The risks remained significant after adjustment for socioeconomic, behav- ioral, and clinical variables.50 The mechanisms underly- ing poorer outcomes with unemployment are not clear. In this study, time of entry into the workforce, which could suggest educational differences or health difficul- ties, was not significantly associated with outcomes.50 A possible explanation is that of cumulative stress, be- cause worse outcomes were seen with additional epi- sodes of job loss and increased time spent unemployed. One limitation of the study was an older cohort (me- dian age, 62 years) that may not be representative of the overall workforce.50

ENVIRONMENTAL FACTORS Neighborhood socioeconomic characteristics, in addi- tion to individual SES, have been associated with CVD risk factors, adverse events, and mortality.15–17 A popu-

lation analysis of the Atherosclerosis Risk in Commu- nity study showed that living in disadvantaged areas is linked to higher incidence of CHD after controlling for individual income, education, and employment sta- tus.17 The findings were supported by a recent analysis of data from the Jackson Heart Study, which found an association between neighborhood disadvantage and cumulative biological risk, a score derived from biomarkers representing cardiovascular, metabolic, inflammatory, and neuroendocrine health.51 The en- vironmental impact of health status and outcomes is driven by both physical and social attributes.16,52 Physi- cal features of neighborhoods include the presence of sidewalks or recreational spaces, access to trans- portation, and availability and cost of healthy foods, whereas social attributes include safety, deprivation, social support, and lack of community cohesion.16 So- cioeconomic differences in neighborhood characteris- tics can impact the availability of resources and influ- ence promotion or maintenance of a healthy lifestyle. Favorable neighborhoods are associated with reduced cardiovascular risk factors, because long-term expo- sure to environments with greater access to physical activity and healthy food was associated with a lower incidence of diabetes mellitus and a lower prevalence of overweight or obesity.53,54 Other social character- istics, including neighborhood crime, also contribute to cardiovascular risk. In multiethnic populations, high individual- and neighborhood-level safety was associ- ated with decreasing body mass index over time.55 In contrast, poorly rated physical environments based on walking environment, availability of healthy food, safety, aesthetics, and social coherence were associ- ated with elevated depressive symptoms and greater increase in waist circumference in individuals living in those neighborhoods.56

Poor dietary options and the increased cost of healthy food may also contribute to the increased CVD risk of disadvantaged neighborhoods. Low-income ar- eas have fewer food outlets and supermarkets, which results in limited access to fresh fruits and vegeta- bles.57,58 The cost of healthy food is also higher in poor areas with limited access, in part because of the lower prevalence of supermarkets that typically offer lower prices and a variety of brand options.59,60 Low-income areas lacking access to healthy, affordable foods are known as food deserts, which are associated with diet- related chronic diseases and obesity.61 There are also racial disparities in food availability, because neighbor- hoods with a high prevalence of blacks tend to have more fast-food restaurants,59 fewer supermarkets,60 and fewer healthy options.62

Neighborhood characteristics can change with time and provide additional insight into the relationship between environmental factors and cardiovascular health. Recent results from a longitudinal study with

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a 12-year follow-up period showed that increasing the density of neighborhood healthy food resources was associated with lower coronary artery calcium over time. However, changes in other neighborhood characteristics, including walking and social environ- ment, were not associated with changes in coronary artery calcium.63 Further longitudinal studies have demonstrated that neighborhoods with favorable physical activity increased individual activities and im- proved cardiovascular risk factors.64,65 However, previ- ous studies also showed that individuals often move into neighborhoods with similar SES across their life course, which impairs attempts to establish a causal relationship between environment and CVD.66,67 Un- fortunately, a recent update by the US Department of Agriculture showed relatively small changes in low- income and low-access neighborhoods between 2010 and 2015 data.68 Disadvantaged communities must be a priority to effectively reduce CVD disparities in indi- viduals with low SES.

PSYCHOSOCIAL FACTORS AND CVD OUTCOMES Psychosocial factors, including stress and depression, are strongly associated with adverse CVD outcomes, and growing evidence suggests they may disparately affect individuals of low SES.69,70 In analysis of the RE- GARDS study (Reasons for Geographic and Racial Dif- ferences in Stroke), a prospective observational cohort in the United States, individuals earning <$35 000 an- nually who reported both stress and depressive symp- toms had a 48% higher risk of developing CVD and a 33% increased risk of all-cause mortality after ad- justment for socioeconomic, clinical, and behavioral factors.69 The association was not present in subjects earning ≥$35 000 per year.69 Likewise, a study of psy- chological distress (depression, anxiety, and stress) demonstrated that the risk of CHD mortality was in- creased in those with low (hazard ratio, 1.31; P=0.001), but not high, SES (P=0.107).70 The disparity in risk may related to inadequate social or material resources to cope with stressful events and higher rates of adverse health behaviors, including smoking and physical inac- tivity, that are associated with stress and depression.71,72 The contribution of poor health behaviors in psycho- social distress is supported by a study from Ye et al73 that found the increased risk of myocardial infarction or death in depressed individuals was attenuated after adjustment for behavioral mechanisms, in particular, smoking and physical inactivity. In addition to identifi- cation and treatment of the components of psychoso- cial stress, these findings suggest a role for aggressive targeting of smoking cessation and physical activity in these individuals.

SES AND CVD OUTCOMES BASED ON SEX Women are overrepresented among those living in pov- erty; thus, they are disproportionately affected by the disparities in the distribution of wealth, income, and access to resources that ultimately can affect overall health and quality of life. In the WISE study (Women’s Ischemic Syndrome Evaluation), women with ischemic heart disease in the lowest SES (household income <$20 000/y) were more likely to be uninsured or have public insurance, yet had much higher drug costs and higher 5-year rehospitalization rates in comparison with higher-income women.74 Income had a far greater impact than any other SES measure, including race, education, marital status, or employment status.74 In a universal healthcare system (Southern Alberta, Can- ada), neighborhood SES was associated with the use of cardiac catheterization and 30-day mortality after acute coronary syndrome in women, but this same associa- tion was not seen in men.75

INTERVENTIONS TO IMPROVE HEALTH BEHAVIORS AND RISK FACTORS Programs aimed at improving health in the socially dis- advantaged must first focus on aggressively targeting traditional risk factors that have strong associations with low SES.7 Behavioral counseling to reduce CVD risk factors including cholesterol levels, blood pres- sure, and diabetes mellitus incidence has been proven effective in the general population and is recom- mended by the US Preventive Services Task Force.76,77 Counseling of the family members of a patient with CVD, who are also at higher risk of vascular events, may improve dietary intake and physical activity, but further research into the applicability of these results to individuals with low SES is required. Studies have shown moderate success with smoking cessation pro- grams aimed at patients of low SES.78 Brown et al78 used an Internet-based smoking cessation program to evaluate the success rate between socioeconomic groups and demonstrated a significant improvement in the low-SES cohort that was not realized in the high-SES population.

However, other studies have suggested more lim- ited efficacy in individuals with low SES.79,80 Siren et al79 found that behavioral counseling improved smoking cessation only in a high-education cohort and had no effect in a low-education group. In a study evaluating lifestyle interventions in low-income American Indians and Native Alaskans, the low-income groups had less improvement in body mass index, unhealthy food con- sumption, and physical activity in comparison with the high-income group.80 The study did find an indirect re- lationship between the number of trained staff at each

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location and the success of lifestyle modification.80 Health counseling has been shown to improve diet in individuals with low SES, and interventions focused on the lack of convenient and affordable access to the components of a healthy diet may also be necessary to improve dietary habits in low-SES areas.79

Regular physical activity is associated with a de- creased risk of CVD and its comorbidities.81,82 Likewise, physical inactivity is an independent risk factor for poor CVD outcomes.83 However, despite the known impact of physical activity and inactivity on CVD modulation, fewer than half of US adults met the recommended levels of physical activity in 2011.84 The burden of in- adequate leisure-time physical activity is especially pronounced in individuals of low SES, which may be because of increased occupational responsibilities or reduced access to safe facilities for exercise.85,86 Pro- grams aimed at increasing physical activity have dem- onstrated promising results in individuals with low SES.79,87 The Walk Your Heart to Health program suc- cessfully improved physical activity in a low- to middle- income group consisting primarily of ethnic minorities in Detroit, Michigan.87 The intervention group met 3 times weekly at community sites and walked for an increasing amount of time (45–90 minutes). Physical activity of the group was increased at 8 weeks, and improvements were noted in the cohort’s systolic blood pressure, fasting blood glucose, total cholesterol, waist circumference, and body mass index at 8 weeks that were maintained at 32 weeks.87 Physical activity ap- pears to be an important target in low-SES communi- ties because of its widespread benefits and inherently inexpensive nature; however, physical insecurity (vio- lence, crime) or lack of infrastructure (sidewalks, bi- cycle paths) in the neighborhood social environment may severely impact an individual’s ability to create a sustainable physical activity regimen.88 Thus, policy in- tervention to address such factors in low-SES popula- tions must be addressed in conjunction with efforts to change individual behavior.89

A substantial barrier to the primary prevention of CVD, especially in low-SES groups, is a lack of access to healthcare providers. Given the increasing demands on physicians, strategies have been developed to better appropriate available resources. One effective commu- nity-based strategy using this paradigm is task shifting, an idea conceived by the World Health Organization as early as 1980 and defined as redistributing primary care responsibilities from physician to nonphysician provid- ers.90 Although a dearth of evidence exists for the use of task shifting in HIC, the trial by Adeyemo et al91 in Nigeria, a LMIC, demonstrated a reduction in systolic blood pressure from a preintervention mean of 168/92 to a goal of <140/90 in 66.7% of patients by using nurse-driven task shifting in comparison with 65.4% of patients receiving usual medical care. Task shifting can

be further extended to include health workers without formal healthcare training, known as community health workers. Community health workers play a valuable role in cost-effective screening for CVD in low-resource countries and communities.92,93 Given the constraints of modern medical practice, task shifting may have utility for CVD screening and risk factor improvement in areas with reduced resources.

Numerous studies have evaluated the role of com- munity interventions on major adverse cardiovascular events and risk factors. Mass media negatively portray- ing tobacco reduces smoking prevalence by ≈2%.94 Tobacco cessation rates can be further impacted by in- creasing prices of tobacco products and state programs to provide nicotine replacement therapy.94 Task shifting the role of smoking cessation management to a com- munity pharmacist increased the quit rate from 2.7% to 14.3% in study participants.94 Similar effects are seen with mass media advocacy for salt restriction and dietary modification.94 Subsidization of healthy foods is another community-level intervention that has demon- strated benefit in low-income individuals. Reducing the cost of healthy foods has been shown to improve diets and reduce the barriers to a healthy diet in food des- erts.95 Similarly, taxation of unhealthy foods decreases their consumption.95 A combined strategy can be used to improve diets in at-risk communities. Environmental engineering, including construction of new supermar- kets to increase access to healthy foods, still lacks ad- equate data to support its use.95

Heart disease exhibits regional clustering in the Unit- ed States (Figure 2, map created using the Interactive Atlas of Heart Disease and Stroke).96 Geomapping, the identification of geographic hot spots of individuals at high risk for CVD, may be used in the future to target communities that would benefit from aggressive com- munity-based interventions.97 Geomapping has dem- onstrated promising early results in Sweden for identi- fication of at-risk populations for diabetes mellitus and could be adapted to provide increased screening and treatment services for low-SES communities with a high prevalence of CVD risk.98

Strategies for identifying and improving health dis- parities in the United States were addressed in a Think Tank meetin

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